Reports and Papers

GIS and simulation models for Water Resources Management:
A case study of the Kelantan River, Malaysia

Published in: GIS Development, August 2002, Vol.6/8, 39-43.

ABSTRACT
The Kelantan river drains the province of Kelantan in north-eastern peninsular Malaysia. A catchment of about 12,000 km2 (upstream of Guillemard bridge) and an altitude difference of more than 2100 m generates an average runoff of about 500 m3/sec, with the variations of the local Monsoon climate. The variability of rainfall with extreme monthly values between 0 and 1750 mm in dry and wet months, respectively, already suggest the main problem: reliability of water resources for the rice paddies that supply about 12 % of national production. Droughts and floods that affect the efficiency of the irrigation system, continuing changes in land use, and the potential of water pollution from intensive agriculture pose a range of problems that require innovative tools for their solution.
WaterWare (https://ess.co.at/WATERWARE/) is a management information system based on a range of linked simulation models that utilize data from an embedded GIS, monitoring data including real-time data acquisition, and an expert system. Accessible in a local area network from a central server, and alternatively through the Internet for remote clients (http://80.120.147.30/KELANTAN/) , the system uses a graphical interface to provide interactive decision support information for water resources planners and policy makers.

INTRODUCTION

Water resources are at the heart of sustainable development in many regions of the world. Water of sufficient quantity and quality is an essential resource for agriculture, industry, and tourism, but also for everyday life in cities and villages. A growing population and a growing economy not only lead to increasing demand for water, they also cause increasing pollution that may threaten the very water resources this growth depends on and thus threaten the sustainability of development (Brookfield and Byron, 1993).

Water resources are distributed in time and space, and their availability may vary greatly from time to time and place to place. This variability causes problems: not enough or too much, drought or flood, and not of the right quality, i.e., polluted: these are the main issues to be addressed.

SPATIAL PROBLEMS AND SPATIAL SOLUTIONS

The basic unit in water resources management is the river basin or hydrographic catchment, and the network of draining channels, the river network that collects and conveys surface water. River reaches, dams and reservoirs, diversion and pumping stations, water works and secondary distribution networks are all spatially distributed elements of this system. Underneath, we find the unsaturated and saturated zones of groundwater aquifers, usually contributing considerable quantities of high quality water with quite different, much slower storage and flow characteristics.

The elements of water resources management are distributed in space. Their location, surrounding, and spatial relationships are critical for the resulting flow characteristics and the quality, of the water resources and thus their availability for different types of use. River basin management has obvious spatial dimensions, since it is focused on a spatial unit, the hydrological catchment, in the first place. Consequently, geographic information systems are one of the tools that can be used for their analysis. This makes the use of GIS, and its integration with traditional water resources models, and obvious strategy for the development of river basin management systems (Maidment 1996, Fedra and Jamieson, 1996).

While the GIS is used to capture, analyse, and display spatial data, the models provide the tools for complex and dynamic analysis. Input for spatially distributes models, as well as their output, can be treated as map overlays and topical maps (Fedra,1994) . The familiar format of maps supports the understanding of model results, but provides also a convenient interface to spatially referenced data. And expert systems, simulation and optimisation models add the possibility for complex, and dynamic analysis to the GIS.

One major challenge in building effective river basin information systems is the integration of dynamic models with the capabilities of GIS. The GIS can provide a common framework of reference for the various tools and models addressing a range of problems in river basin management, supply distributed data to the models, and assist in the visualisation of spatial model results in the form of topical maps. In a multi-media framework, it can also provide a common interface to the various functions of an integrated river basin information and decision support system. This interface has to translate the data and model functionality available into information that can directly support decision making processes (Fedra, 1995).

FUNCTIONS AND TOOLS

WaterWare organises the data describing a river basin in terms of spatial objects: they include elements such as monitoring stations and their associated time series of measurements, sub-catchments and irrigation districts, the river network with it nodes and connecting reaches, as well as the various simulations models and their scenarios (Fedra and Jamieson, 1996a,b, Jamieson and Fedra 1996a,b). With all objects geo-referenced and the models spatially distributed, the embedded GIS is a central component.

The embedded GIS

The map layers used in WaterWare either provide background for spatial reference and orientation, or direct data input for the simulation models. Examples for the latter are the digital elevation model (DEM), land use maps, and the river network.

The embedded GIS offers tools for layer selection and stacking, zooming, color editing, a four window mode for map comparison, 3D display of the DEM with any map draped over the elevation data, and read-back functions for locations, distances, or areas.

FIGURE 1,2: GIS examples, four windows and 3D DEM display

Monitoring time series.

Historical data of rainfall, river flow, and air temperature, as well as water quality are stored for the various monitoring stations. Continuous ongoing measurements from selected stations are transferrd by GSM phones and incorporated into the data base in real-time to provide an accurate and up to date picture of the situation (http://jpsscada.moa.my/kelantanw.htm).

These hydrographic and hydrometeorological observation data are not only analysed in their own right, they also form the input for the various simulation models.

FIGURE 3,4,5,6: Time-series analysis (flow), histogram, spatial homogeneity, spatial interpolation

Analysis of droughts

A major problem for water resources management are droughts: prolonged periods of below-average rainfall that lead to low soil moistures, lowering of the groundwater table, and, most importantly, low flow in the river. This, in turn, leads to a combination of increased water demand for irrigation and a low availability of irrigation water: below a certain low-flow level, pumping water out of the river in fact becomes impossible, the pumps fall dry. Based on a model by Jamaluddin et al.,(2000), WaterWare links the time series of rainfall observations to a drought analysis module.

Sub-catchment and runoff modelling

The water resources model needs river flow at all of its start nodes, representing inputs. These can be well fields, where groundwater enters the surface water budget, or sub-catchments. For the latter, a rainfall-runoff model provides data for ungaged catchments, but also the possibility for scenario analysis of land-use changes or long-term climate change.

Data such as catchment boundaries, elevations and slopes, land use, as well as rainfall inputs are automatically taken from the GIS and time series data base, respectively.

FIGURE 7: Rainfall-Runoff Model results

Irrigation water demand

Irrigated agriculture, and rice paddies in particular, are the dominant consumer of water, by far exceeding industrial and domestic demand. The water demand in a given year depends on the naturally available water through rainfall, but also the areas and crop varieties to be irrigated, irrigation technology, the conveyance systems (e.g., lined versus unlined irrigation canals), and operational control. A specific simulation model is used to predict the water demand for any of the irrigation districts in the basin.

FIGURE 8,9: Irrigation Water Demand Model: irrigation district object and simulation model

Water resources allocation

The central model in the WaterWare system is a dynamic, water resources model that computes a daily water budget for all nodes in the river network. The model computes water budgets in terms of demand and supply, routing the water from the start nodes (sub-catchments) to the demand nodes (irrigation districts and cities) and ultimately the sea. Different allocation strategies and policies can thus be tested for the effectiveness and efficiency.

By adding a simple estimation routine for the net economic benefit for different types of water use, an overall economic optimisation of the water allocation is possible.

FIGURE 10: Water Resources Management model results

River water quality

The flow in the individual reaches of the river network is a major determinant for water quality: dilution is a major factor in pollution. The dynamic water quality model describes the balance of organic load, measured as BOD (biological oxygen demand) and dissolved oxygen, as well as any arbitrary pollutant, conservative or undergoing first-order decay. Examples would be agrochemicals such as fertilizers and pesticides, or the salts leached out from irrigated agricultural soils. Sources of pollution are major settlements and their waster treatment plants, as well as any major industrial or agricultural water users that return used process or irrigation water to the system. The model treats both points sources of pollution, as well as lateral inflow from diffuse sources.

Groundwater flow and quality

Similar to the contamination of surface water, groundwater pollution can result from the large-scale application of fertilizers and agrochemicals. Waste management in the form of badly managed land fills is an other potential source of groundwater pollution in the humid tropics. The groundwater model describes the first, shallow aquifer that is directly exposed to non-point source pollution.

The major driving forces include the spatially distributed recharge from rainfall depending on land use, infiltration or exfiltration from and to the river, and the pumping of groundwater in shallow wells, that constitute the majority of small, domestic wells. Spatially varying characteristics of the aquifer and landuse are directly taken from the GIS. Excessive levels of nitrates that can pose a long-term health hazard are the major problem.

FIGURE 11: Ground Water Model results

Environmental Impact assessment

A water resources management system is subject to structural changes such as new reservoirs, or policy changes resulting in a modified water allocation pattern. Any such project or policy change will have a range of environmental impacts, positive or negative. For the screening level assessment of such projects, and new reservoirs in particular, WaterWare offers a rule-based expert system for environmental impact assessment (Fedra et al., 1991). A checklist of potential problems is used together with a set of rules for the evaluation, with the data coming from the GIS, the object data base, and model results. The inference engine uses a combination of forward and backward chaining (Fedra and Winkelbauer, 2002), to provide a classification of all potential problems relevant for a given project and environment.

IMPLEMENTATION

Beyond the implementation of the system on a PC server under Linux, accessible from the console and any computer in the local area network, parts of WaterWare are also accessible through the Internet. All major modules export results as HTML files with their associated graphics into the directory tree of a web server (http://80.120.147.30/KELANTAN/) running under Apache. Using XML/HTML, Javascript and Java applets, this implementation supports distributed, remote clients also on low-bandwidth connections, and thus increases the potential group of users considerably.

DISCUSSION

WaterWare is an object oriented information and decision support system for river basin management. The basic data framework combines a hybrid GIS as the overall structure with classes of objects, including river basin elements, models and model scenarios, and tasks or decision problems.

River basin elements are spatially referenced, and represent, for example, sub-catchments, reservoirs, treatment plants, river reaches, etc. From the GIS perspective, they are polygons, lines, points, or regular cell grids. Their state, in a context defined by other objects in the system, is determined by a set of methods, which are models or sets of rules for an embedded expert system. Tasks are specific, problem oriented views of river basin objects or combinations of objects. They present their state, usually over time, given a number of decision variables or scenario assumptions, to the user to support planning or management decisions.

The various objects are linked explicitly, eg., a reservoir might be linked to the sub-catchment that provides its inflow, an observation station that monitors the hydro-meteorological data, and an irrigation district it supplies water to. Models such as a rainfall-runoff model or an irrigation water demand estimation model are used to update the state of these respective objects, and thus provide inputs (time series of demand or supply) to a water resources model. The water resources model, in turn, provides input to a water quality model, that again operates in the context of other objects such as discharge nodes (treatment plants, industries, municipalities), or extraction and monitoring points.

Models are embedded, as methods, with the respective objects. Rules are used to configure the scenarios and estimate parameters. The models' operation can either be transparent, when a task requires an update on an object, or explicit, when the task is defined in terms of model scenario analysis.

The GIS, with the underlying spatial data such as land use, geology, and topography, also provides the display functions; spatial model output is dynamically mapped onto the map background as animated topical map coverages. Textual, numerical, and pictorial attributes of an object, and meta data providing background information to the user, are accessible through a multi-media hypertext system, that objects use to present themselves to the user. GIS, data base, and model interface are thus fully integrated, and present a unified graphical and symbolic representation of a river basin to the user. This interface supports an easy to learn, exploratory and experimental access to a large and complex information and decision support system. The multi-media nature of the system's interface also makes its extension into a networked client/server version for access through the World Wide Web straightforward, which increases the group of potential users, and eventually, the planning and management decision they make.

REFERENCES

Brookfield, H. and Byron, Y. [eds.] (1993): South-East Asia�s Environmental Future: the search for sustainability. 452 pp, United Nations University Press, Tokyo, New York, Paris.
Fedra, K. (1995): Distributed Models and Embedded GIS: Strategies and Case Studies of Integration. In: Goodchild, M.F., Steyart, L.Y., Parks, B.O., Johnston, C., Maidment, D., Crane, M. and Glendinning, S. [Eds.], GIS and Environmental Modeling: Progress and Research Issues, pp. 413-417. GIS World Books, Fort Collins, CO. 1996.
Fedra, K. (1994): GIS and Environmental Modeling. In: Goodchild M.F., Parks B.O. and Steyaert L.T., [eds.] Environmental Modeling with GIS, 35-50, Oxford University Press, New York.
Fedra, K. and Feoli, E. (1998): GIS Technology and Spatial Analysis in Coastal Zone Management. EEZ Technology, Ed. 3, 171-179.
Fedra, K. (1996): Multi-Media Environmental Information Systems: Wide-Area Networks, GIS, and Expert Systems. GIS: Geo-Informations-Systeme Vol/Nr. 9/3, 3-10.
Fedra, K. and Jamieson, D.G. (1996): The WaterWare decision-support system for river basin planning: II. Planning Capability. Journal of Hydrology 177 (1996) 177-198.
Fedra, K., and Jamieson, D.G. (1996): An object-oriented approach to model integration: a river basin information system example. In: Kovar, K. and Nachtnebel, H.P. [eds.]: IAHS Publ. no 235, pp. 669-676.
Fedra, K. and Winkelbauer, L. (2002): A hybrid expert system, GIS and simulation modelling for environmental and technological risk management. Computer-Aided Civil and Infrastructure Engineering, 17 (2002) 131-146.
Jamalluddin bin Shaaban, A., Zaiton Ibrahim, Z., An, H.K., Jabir bin Kardi (2000): The 1998 Langat Valley drought and teleconnection with ENSO events (private communication).
Jamieson, D.G. and Fedra, K. (1996): The WaterWare decision-support system for river basin planning: I. Conceptual Design. Journal of Hydrology 177 (1996) 163-175.
Jamieson, D.G. and Fedra, K. (1996): The WaterWare decision-support system for river basin planning: III. Example Applications. Journal of Hydrology 177 (1996) 199-211.
Maidment, D. (1993): GIS and hydrological modeling. In: M.F. Goodchild, B.O. Parks and L.T. Steyaert [eds.] Geographic Information Systems and Environmental Modeling. Oxford University Press.

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